New Mexico

LMI Qualification:

• Medicaid
• SNAP
• LIHEAP
• First-time home owner programs
• Affordable housing facilities
  • HUD data: https://resources.hud.gov/#layers-menu
  • state specific to supplement: https://housingnm.org/find-housing/rentals/affordable
• Low-income housing
• State and federal income tax credit
• Entire multi-family housing project may qualify if the entire load can be proved to be low-income subscribers, with consent of all tenants of record.
• LMI - 80% of AMI

Public Housing

# nm_data <- read_excel("nm_public_housing.xlsx")
# 
# register_google( key='AIzaSyAoldbWBmW88JZSqiNDW4cKDgIbHI_umco')
# 
# library(ggmap)
# 
# # Assuming your 'nm_data' dataframe has columns 'Address' and 'Address 2'
# # Create a new column to store the full address (combining Address and Address 2)
# nm_data$full_address <- paste(nm_data$Address, nm_data$`Address 2`, sep = ", ")
# 
# # Use geocode() to get latitude and longitude for each address
# geocoded_data <- geocode(nm_data$full_address)
# 
# # Add latitude and longitude columns to the original dataframe
# nm_data$Latitude <- geocoded_data$lat
# nm_data$Longitude <- geocoded_data$lon
# 
# nm_data <- nm_data %>%
#   filter(!is.na(Longitude))
# 
# nm_data <- st_as_sf(nm_data, coords = c("Longitude", "Latitude"), crs = st_crs(nm_blocks))

# st_write(nm_data, "nm_public_housing.shp")

nm_public_housing <- st_read("nm_public_housing.shp")

## Reading layer `nm_public_housing' from data source 
##   `/Users/jacobford/Library/CloudStorage/GoogleDrive-jake@solstice.us/Shared drives/Product | Jake/Geocoding/Qualified LMI by Utility Zones/lmi_by_utility/nm_public_housing.shp' 
##   using driver `ESRI Shapefile'
## Simple feature collection with 226 features and 6 fields
## Geometry type: POINT
## Dimension:     XY
## Bounding box:  xmin: -108.8368 ymin: 31.79585 xmax: -103.048 ymax: 36.91717
## Geodetic CRS:  NAD83

library(leaflet.extras)


nm_pub_in_util <- nm_public_housing %>%
  st_point_on_surface() %>%
  st_join(temp_util %>% select(util_name = NAME)) %>%
  filter(!is.na(util_name))

## Warning in st_point_on_surface.sf(.): st_point_on_surface assumes attributes
## are constant over geometries of x

## Warning in st_point_on_surface.sfc(st_geometry(x)): st_point_on_surface may not
## give correct results for longitude/latitude data

  map %>%

  addMarkers(data=nm_public_housing,
                   group="Public Housing",
                #   color="black",
                #   radius=2,
                   popup=paste("Name: ", nm_public_housing$Name)) %>%
  addMarkers(data = nm_pub_in_util,
             group="Public Housing in Utility Zones",
           #  color="red",
            popup=paste("Name: ", nm_pub_in_util$util_name)) %>%


  addLayersControl(
    overlayGroups=c("80% AMI Percent", "80% AMI Count", "Utility Zone", "SNAP", "Medicaid", "Public Housing", "Public Housing in Utility Zones"),  # Update the order for consistency
    options = layersControlOptions(collapsed = FALSE)
  ) %>%
  hideGroup("80% AMI Percent") %>% hideGroup("SNAP") %>% hideGroup("80% AMI Count") %>% hideGroup("Medicaid") %>% hideGroup("Public Housing in Utility Zones")

## Warning: sf layer has inconsistent datum (+proj=longlat +datum=NAD83 +no_defs).
## Need '+proj=longlat +datum=WGS84'

## Warning: sf layer has inconsistent datum (+proj=longlat +datum=NAD83 +no_defs).
## Need '+proj=longlat +datum=WGS84'